Key Responsibilities : - Manage Data - Building the next generation extremely large, scalable and fast distributed systems to ingest, organise and manage all data at scale efficiently - Own and optimize data architecture to address the data needs of our rapidly-growing business - Setup, manage &amp; maintain data lakes and warehouses across the entire organisation - Setup, manage &amp; maintain BI solutions &amp; tools to analyse data - Setup data streaming systems to ingest and automate data at scale - Ensure quality and workability of all data Analyse Data : - Architect, build, and launch new data models that provide intuitive analytics to various teams across multiple tech stacks - Build and integrate robust data processing pipelines for enterprise-level business analytics - Work with customers of the data team in a fast paced environment understanding the business requirements and implementing analytical solutions. - Work with engineering, product and business owners to develop and define key business questions and to build data sets that answer those questions - Assist other team members with reporting, debugging data accuracy issues and other related functions Model data : - Leverage the understanding developed by introspecting the data to build data models for product functioning and product enhancement - Build predictive data models for recommendation, classification etc - Identify the right model for every use case - simple empirical model to a deep learning based model and everything in between - Devise strategies to test and trial run the models built - Continuously monitor the performance of models and enhance - Own the entire process end to end from data collection, cleaning, feature engineering, algorithm/tool selection, model testing to the final model Deploy Data : - Translate data models into efficient engineering code to deploy at scale efficiently - Build systems for the product to leverage data and models based on the data in real time - Meticulously develop and deploy production data pipelines (batch + real time) - Analyse on model's decision data, to deepen intuition, for best integration of machine learning model recommendations - Skill fully implement performance engineering of relevant big data systems - Building a team which is thoughtfully developing, improving, and owning data systems that empowers the entire organisation with data - Lead and provide coaching to the data engineering team. Lead by example, demonstrating best practices for unit testing, CI/CD, performance testing, capacity planning, documentation, monitoring, alerting, and incident response - Actively participate in key business, architectural and technical decisions Desired Candidate's Profile : - Relevant Experience in a data focused role - 6+ years - Strong hold on SQL - Prior experience of building a data lakes / warehouses - Strong background in new age AWS stack (S3, EMR, Redshift) or traditional BI &amp; DW with interest in data mining and ability to sieve emerging patterns and trends from large amount of data. - Experience with data modeling, data warehousing, and building ETL pipelines - Extensive experience in dimensional modeling, excellent problem solving ability dealing with huge volumes of data and a short learning curve - Experience in analyzing data to draw business-relevant conclusions and in data visualization - Experience leading and influencing the data strategy of your team or organization - Strong written and verbal communication skills including technical writing skills - Strong background in statistical concepts and calculations - Innovative and strong analytical and algorithmic problem solvers. - Experience with modern data warehousing products like Redshift, Bigquery, Snowflake. - Proficiency with analysis tools like Excel, SQL, Python (Knowhow of AWS infra is a plus point) - Acquaintance with concepts of BI - MicroStrategy, QlikSense, Tableau - Experience working with Big Data streaming services such as Kinesis, Kafka etc - Experience working with NoSQL data stores such as HBase, Mongo etc - Experience working with Hadoop or Big Data processing frameworks (Spark, Hive, Nifi, Spark-Streaming, Flink, etc.) - Advanced Excel &amp; VBA scripting - Excellent coding skills in Scala or Python - Experience with data science libraries such as Scikit-learn, Pandas, Numpy, Scipy, Spacy, NLTK, H2O, Tensorflow and Pytorch. - Team Handling

Mumbai

Noida

Indus OS - Head - Data Engineering & Analytics 

Indus OS - Head - Data Engineering & Analytics  ,Job Description for Indus OS - Head - Data Engineering & Analytics  in Indus Os in  Mumbai Noida for (7-12) years of experience. Apply Now!

Job Description for Indus OS - Head - Data Engineering & Analytics  in Indus Os in  Mumbai Noida for (7-12) years of experience. Apply Now!